Update app.py

app.py

@@ -1,5 +1,4 @@
 import streamlit as st
-from streamlit.state import session_state
 import pickle
 import pandas as pd
 import torch
@@ -51,7 +50,6 @@ st.markdown(
     unsafe_allow_html=True,
 )
 
-
 device = torch.device("cpu")
 
 testing_df = pd.read_csv("testing_df.csv")
@@ -59,13 +57,11 @@ model = CLIPModel().to(device)
 model.load_state_dict(torch.load("weights.pt", map_location=torch.device('cpu')))
 text_embeddings = torch.load('saved_text_embeddings.pt', map_location=device)
 
-# Add this function to initialize the session state
-def init_state():
-    if 'user_input' not in session_state:
-        session_state.user_input = ''
-    if 'chat_history' not in session_state:
-        session_state.chat_history = []
-
+# Initialize the session state
+if 'user_input' not in st.session_state:
+    st.session_state.user_input = ''
+if 'chat_history' not in st.session_state:
+    st.session_state.chat_history = []
 
 def show_predicted_caption(image):
     matches = predict_caption(
@@ -108,8 +104,6 @@ def download_link(content, filename, link_text):
     href = f'<a href="data:application/octet-stream;base64,{b64}" download="{filename}">{link_text}</a>'
     return href
 
-# Initialize the session state
-init_state()
 
 st.title("RadiXGPT: An Evolution of machine doctors towards Radiology")
 
@@ -150,24 +144,24 @@ if uploaded_file is not None:
             st.header("1-to-1 Consultation")
             st.write("Ask any questions you have about the radiology report:")
             
-            session_state.user_input = st.text_input("Enter your question:", value=session_state.user_input)
+            st.session_state.user_input = st.text_input("Enter your question:", value=st.session_state.user_input)
             
-            if session_state.user_input:
-                session_state.chat_history.append({"user": session_state.user_input})
+            if st.session_state.user_input:
+                st.session_state.chat_history.append({"user": st.session_state.user_input})
             
-                if session_state.user_input.lower() == "thank you":
+                if st.session_state.user_input.lower() == "thank you":
                     st.write("Bot: You're welcome! If you have any more questions, feel free to ask.")
-                    session_state.user_input = ''
-                    session_state.chat_history = []
+                    st.session_state.user_input = ''
+                    st.session_state.chat_history = []
                 else:
                     # Generate the answer to the user's question
-                    prompt = f"Answer to the user's question based on the generated radiology report: {session_state.user_input}"
-                    for history_item in session_state.chat_history:
+                    prompt = f"Answer to the user's question based on the generated radiology report: {st.session_state.user_input}"
+                    for history_item in st.session_state.chat_history:
                         prompt += f"\nUser: {history_item['user']}"
                         if 'bot' in history_item:
                             prompt += f"\nBot: {history_item['bot']}"
             
                     answer = chatbot_response(prompt)
-                    session_state.chat_history[-1]["bot"] = answer
+                    st.session_state.chat_history[-1]["bot"] = answer
                     st.write(f"Bot: {answer}")
-                    session_state.user_input = ''
+                    st.session_state.user_input = ''